Information Analysis System, Information Analysis Method, and Information Analysis Program

1. An information analysis system comprising: circuitry configured to select a plurality of threads from a bulletin board service or a social networking service, receive a classification of the plurality of threads as important and unimportant, train a machine learning engine with the threads classified as important and the threads classified as unimportant, analyze, using the trained machine learning engine, importance of a remark included in a thread serving as a group of remarks posted on a network, based on remark data serving as data relating to the remark, for each of the remarks, analyze, using the trained machine learning engine, which of a plurality of preset categories the thread belongs to, based on thread data serving as data relating to the thread, analyze, using the trained machine learning engine, importance of the thread based on the thread data, calculate total importance of the remark based on the importance of the remark and the importance of the thread, store the remark, the total importance of the remark, and a category of the thread including the remark in association with each other for each of the remarks, in a predetermined memory, and retrieve, from the predetermined memory in response to an input, one or more of useful remarks to be presented to a user.

2. The information analysis system according to claim 1 , wherein the circuitry is configured to analyze a remark category indicating which of a plurality of preset categories contents of the remark belong to, for each of the remarks, based on the remark data, and store the remark category of each of the remarks in association with the remark.

3. An information analysis method executed by an information analysis system including circuitry, the information analysis method comprising: selecting, using the circuitry, a plurality of threads from a bulletin board service or a social networking service; receiving, using the circuitry, a classification of the plurality of threads as important and unimportant; training, using the circuitry, a machine learning engine with the threads classified as important and the threads classified as unimportant; analyzing, using the circuitry and the trained machine learning engine, importance of a remark included in a thread serving as a group of remarks posted on a network, based on remark data serving as data relating to the remark, for each of the remarks; analyzing, using the circuitry and the trained machine learning engine, which of a plurality of preset categories the thread belongs to, based on thread data serving as data relating to the thread; analyzing, using the circuitry and the trained machine learning engine, importance of the thread based on the thread data; calculating, using the circuitry, total importance of the remark based on the importance of the remark and the importance of the thread; storing, using the circuitry, the total importance of the remark, and a category of the thread including the remark in association with each other for each of the remarks, in a predetermined memory; and retrieving, using the circuitry, from the predetermined memory in response to an input, one or more of useful remarks to be presented to a user.

4. A non-transitory computer-readable recording medium having stored an information analysis program causing a computer to execute a process comprising: selecting a plurality of threads from a bulletin board service or a social networking service; receiving a classification of the plurality of threads as important and unimportant; training a machine learning engine with the threads classified as important and the threads classified as unimportant; analyzing, using the trained machine learning engine, importance of a remark included in a thread serving as a group of remarks posted on a network, based on remark data serving as data relating to the remark, for each of the remarks; analyzing, using the trained machine learning engine, which of a plurality of preset categories the thread belongs to, based on thread data serving as data relating to the thread; analyzing, using the trained machine learning engine, importance of the thread based on the thread data; calculating total importance of the remark based on the importance of the remark and the importance of the thread; storing the importance of the remark, and a category of the thread including the remark with each other for each of the remarks, in a predetermined memory; and retrieving, from the predetermined memory in response to an input, one or more of useful remarks to be presented to a user.